1. Field of the Invention
The invention relates to electrocardiography and more particularly to computer-supported analysis of selected signal components such as late potentials in electrocardiograms (ECGs), wherein, after preamplification and impedance transformation, signals are incrementally amplified, normalized, digitized, stored in memory, and manipulated by computer to provide temporal and frequency information about selected signal components of waveform segments.
2. Description of the Related Art
After a myocardial infarction, patients are at risk from the occurrence of dangerous disturbances of the cardiac rhythm (ventricular tachycardia). Five to 10% of the post-infarct patients die within one year from sudden rhythmogenically caused cardiac death. Previous methods for identifying this risk group (long-time ECG (Holter ECG) exercise test, ECG at rest) are either not sensitive enough or not specific enough. In the 1970s, minute signal fluctuations (of about 1 to 5 V amplitude) were discovered in the surface ECG during sinus rhythm at the end of the QRS complex, so-called late potentials which occur significantly more frequently in post-infarct patients at risk due to disturbance of rhythm than in patients with a good prognosis.
Verification of these very small potentials reaches the boundary of what is technically possible. Previous methods, utilizing time-domain techniques, use waveform averaging over summation in order to improve the signal/noise ratio. SIMSON's method (reference 1 in Appendix 1), which is the one used most until now, filters the ECG signals bi-directionally by means of a 25-Hz high-pass filter and combines the three channels to form a vector quantity, the filtered QRS complex. The disadvantages of SIMPSON's method are:
a) patients with a bundle-branch block must be excluded; PA1 b) definitions of "abnormal" depend on the noise level; PA1 c) definitions are not uniformly handled by various working groups; PA1 d) individual beats cannot be examined; PA1 e) it is impossible to obtain spatial information on one of the three channels; and PA1 f) high-pass filtering can give rise to false results due to filter overshoots and ringing. PA1 a) high frequency resolution with short waveform segments; PA1 b) power spectrum estimation without the necessity of windowing; PA1 c) ability to delimit late potentials with respect to noise and other interferences; PA1 d) unambiguous definition of abnormal spectra independent of the noise level; and PA1 e) late potentials that are accurately located within the ST portion.
More recent methods for detecting late potentials have become known as results of research in the United States and the Federal Republic of Germany was published (references 2 and 3). These methods are based on the fact that late potentials can be detected by spectral analysis of high-frequency signal components in the ST part of an ECG, a region which otherwise has only low frequency components. These methods utilize Fourier transform techniques for power spectrum estimation.
Although frequency domain analysis through the use of Fourier transform techniques avoids some disadvantages of previously used methods which utilize time domain analysis (compare reference 3, in Appendix 1), there are other problems associated with analysis using Fourier transform techniques:
1. The frequency resolution of short waveform segments is poor. However, longer waveform segments cannot be used in the ECG, because ECG sections which are not of interest would be included and thus interfere with the frequency spectrum.
2. It impossible to locate the late potentials temporally in the necessarily long waveform segment examined.
3. Analysis of late potentials is associated with problems in the ST region still containing steep QRS components; this leads to frequency distortions, because steep edges represent high frequency spectral components that interfere with the frequency spectrum.
4. To reduce spectral leakage effects, window functions are artificially imposed on the signal; this further reduces the frequency resolution and can attenuate or extinguish useful signals at the segment boundaries.
Previous methods used time domain techniques to temporally locate small potentials, but those techniques are susceptible to interference. To alleviate interference problems, frequency domain techniques were employed. Regretfully, this is done at the expense of the ability to temporally locate the verified potentials within the waveform analyzed. A relatively large waveform segment is required for Fourier transform techniques, because the frequency resolution attainable from a waveform deteriorates as waveform size is reduced. Moreover, since a Fourier transform can only operate on a finite waveform segment, acquired waveforms must be truncated in the time domain before being transformed into the frequency domain. As a result, frequency information leaks between frequencies causing the frequency representation to be blurred. Windowing is necessary to alleviate these leakage problems, but this is done at the expense of some frequency information, thereby making the resulting frequency domain representation less blurred but more coarse.
Accordingly, a primary aspect of the present invention is to provide spectral and temporal representations of ECG waveforms that are substantially sharper than those obtainable with conventional means.